The Impact X-Factor

Just time for a quick (yet still rather tardy) post to direct your attention to an excellent polemical piece by Stephen Curry pointing out the pointlessness of Journal Impact Factors. For those of you in blissful ignorance about the statistical aberration that is the JIF, it’s basically a measure of the average number of citations attracted by a paper published in a given journal. The idea is that if you publish a paper in a journal with a large JIF then it’s in among a number of papers that are highly cited and therefore presumably high quality. Using a form of Proof by Association, your paper must therefore be excellent too, hanging around with tall people being a tried-and-tested way of becoming tall.

I won’t repeat all Stephen Curry’s arguments as to why this is bollocks – read the piece for yourself – but one of the most important is that the distribution of citations per paper is extremely skewed, so the average is dragged upwards by a few papers with huge numbers of citations. As a consequence most papers published in a journal with a large JIF attract many fewer citations than the average. Moreover, modern bibliometric databases make it quite easy to extract citation information for individual papers, which is what is relevant if you’re trying to judge the quality impact of a particular piece of work, so why bother with the JIF at all?

I will however copy the summary, which is to the point:

So consider all that we know of impact factors and think on this: if you use impact factors you are statistically illiterate.

• If you include journal impact factors in the list of publications in your cv, you are statistically illiterate.
• If you are judging grant or promotion applications and find yourself scanning the applicant’s publications, checking off the impact factors, you are statistically illiterate.
• If you publish a journal that trumpets its impact factor in adverts or emails, you are statistically illiterate. (If you trumpet that impact factor to three decimal places, there is little hope for you.)
• If you see someone else using impact factors and make no attempt at correction, you connive at statistical illiteracy.

Statistical illiteracy is by no means as rare among scientists as we’d like to think, but at least I can say that I pay no attention whatsoever to Journal Impact Factors. In fact I don’t think many people in in astronomy or astrophysics use them at all. I’d be interested to hear from anyone who does.

I’d like to add a little coda to Stephen Curry’s argument. I’d say that if you publish a paper in a journal with a large JIF (e.g. Nature) but the paper turns out to attract very few citations then the paper should be penalised in a bibliometric analysis, rather like the handicap system used in horse racing or golf. If, despite the press hype and other tedious trumpetings associated with the publication of a Nature paper, the work still attracts negligible interest then it must really be a stinker and should be rated as such by grant panels, etc. Likewise if you publish a paper in a less impactful journal which nevertheless becomes a citation hit then it should be given extra kudos because it has gained recognition by quality alone.

Of course citation numbers don’t necessarily mean quality. Many excellent papers are slow burners from a bibliometric point of view. However, if a journal markets itself as being a vehicle for papers that are intended to attract large citation counts and a paper published there flops then I think it should attract a black mark. Hoist it on its own petard, as it were.

So I suggest papers be awarded an Impact X-Factor, based on the difference between its citation count and the JIF for the journal. For most papers this will of course be negative, which would serve their authors right for mentioning the Impact Factor in the first place.

PS. I chose the name “X-factor” as in the TV show precisely for its negative connotations.

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